CMS Recognizes the Need to Improve E&M Guidelines

How many of us remember the 90010? That was an evaluation and management (E&M) code in 1991, prior to the revision that still haunts us today.

Back then, in the good old days, E&M codes were qualitative in nature, meaning that their use was based on physicians’ interpretation of the level of care being provided to their patients. Back then, the E&M coding category took up four pages in the Current Procedure Terminology (CPT) manual. Back then, the decision on which code to use was pretty straightforward, and we relied upon the physician’s judgement to select the proper code.

But in 1992, it all changed. Just one year later, the section on E&M coding in the American Medical Association’s (AMA’s) CPT® code manual went from four pages to 44 pages. Then, in 1996, in what felt like a slap to the face of providers struggling to navigate a new system that was administratively complex and medically unnecessary, the Kassebaum-Kennedy bill was passed, criminalizing the miscoding of medical services.

The big change was a move from E&M codes being qualitative (1991) to becoming quantitative (1992). That latter year was the year in which the resource-based relative value scale (RBRVS) was born, with the purpose of allowing providers to assign a quantitative value of cost and/or resource consumption to every medical service and procedure that was directly initiated, supervised by, or participated in by a physician.

What really surprised me during those days was that the AMA seemed to be a driving force behind the Health Care Financing Administration (HCFA, now CMS, or the Centers for Medicare & Medicaid Services) in its move to complicate the patient encounter. And this occurred even in the face of resounding objections from the physician community.

In 1996, we got the 1995 E&M guidelines. In 1998, the 1997 E&M guidelines were published. To the uninitiated, one would think that one of these would have replaced the other, but such was not the case. In fact, it resulted in there being two sets of guidelines, and physicians could choose which to employ.

The 1997 guidelines were a bit more flexible when recording the history of present illness (HPI) portion of the key component for history. But the 1995 guidelines indicated that the physician must use the elements of HPI when completing the history portion. The physical exam rules are quite different between the two sets of guidelines, and it was incumbent on the physician or coder to determine which presented the most accurate picture of the encounter.

In fact, I did an analysis once on the complexity of coding for an encounter, and the way I figured it, a physician has more than 1,500 decision points to overcome when coding for a single patient visit. In fact, it is my opinion that coding for an encounter is likely more complex than the clinical portion of the encounter, and selecting the wrong code can result in greater risk to the provider than that of misdiagnosing the patient. No wonder change is in the air.

In March 2016, a total of 10 medical societies penned a letter to Sean Cavanaugh, then deputy administrator and director for CMS. In this letter, these societies asked for CMS to expand the breadth of E&M codes. They said the following in their opening sentence:

“We believe that the existing office codes (CPT 99201-5 and 99211-5) no longer accurately or adequately reflect the work currently provided to and required by Medicare beneficiaries.”

In fact, they were asking CMS to consider making the system more complicated, not less complicated, which was surprising to some. I’m not saying that this wasn’t needed, I’m just saying it might have been nice to standardize and simplify the existing system before moving forward with adding more codes and more pages to an already confusing mix. Today, along comes the 2018 Proposed Medicare Fee Schedule, wherein CMS “promises” to “consider” changes to the guidelines for E&M codes. “Promises and considers.”

Hmmm. Where have I heard those words before? Anyway, they are soliciting comments and proposals on ways to change E&M coding guidelines for the better. Recently, in a news conference, John Fleming, MD, deputy assistant secretary for health technology reform with the U.S. Department of Health and Human Services (HHS), admitted that the burden the current guidelines place on physicians is out of control.

“Now that EHRs are online, we see how the two (EHRs and E/M coding guidelines) create even more problems: we get voluminous, sometimes nonsensical health notes that can be unreadable or make it difficult to determine where the real information is,” Fleming said.

And even though he ended his sentence with a preposition, I think he did a good job at making his point. I read somewhere that it takes more than 10 years for a positive clinical discovery to make it to the physician’s office. It seems it took more than 20 years for the need for change to make it to CMS.

But alas, maybe (and I emphasize “maybe”) it is here.

Maybe it’s time to stop worrying about how neatly we can fit E&M codes into computer code and quantitative models and focus more on how they can accurately and simply describe the level and type of care provided to a patient during the encounter.

I’m not a coding expert, but then again, if we had a more reasonable system, maybe I wouldn’t have to be one. Who knows. I just hope that everyone who has an idea on how to make E&M coding less burdensome and more clinically precise will take the time to comment on these new proposed rules.

And that’s the world according to Frank!

PROGRAM NOTE: Evaluation and management (E&M) services are the subject of a new four-part, on-demand webcast series available for download Sept. 22. Register now at the RACuniversity bookstore.

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Frank Cohen, MPA

Frank D. Cohen is Senior Director of Analytics and Business Intelligence at VMG Health, LLC, and is Chief Statistician for Advanced Healthcare Analytics. He has served as a testifying expert witness in more than 300 healthcare compliance litigation matters spanning nearly five decades in computational statistics and predictive analytics.

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